FixedEffectsModel
represents an allometric model that only uses fixed
effects.
A named list containing one element, with a name representing the response
variable and a value representing the units of the response variable
using the units::as_units
function.
A named list containing the covariate specifications, with names
representing the covariate name and the values representing the units of
the coavariate using the units::as_units
function
A function that takes the covariate names as arguments and returns a prediction of the response variable. This function should be vectorized.
A named list of parameters and their values
An optional named list of descriptors that describe the context of the allometric model
A string containing an optional custom response definition, which is used instead of the description given by the variable naming system.
An optional named list of custom covariate definitions that will supersede
the definitions given by the variable naming system. The names of the list
must match the covariate names given in covariates
.
An object of class FixedEffectsModel
response_unit
A one-element list with the name indicating the response
variable and the value as the response variable units obtained using
units::as_units()
covariate_units
A list containing the covariate names as names and
values as the values of the covariate units obtained using
units::as_units()
predict_fn
The prediction function, which takes covariates as arguments and returns model predictions
descriptors
A tibble::tbl_df
containing the model descriptors
set_descriptors
A tibble::tbl_df
containing the set descriptors
pub_descriptors
A tibble::tbl_df
containing the publication
descriptors
citation
A RefManageR::BibEntry
object containing the reference
publication
covariate_definitions
User-provided covariate definitions
model_type
The model type, which is parsed from the response_unit
name
parameters
A named list of parameters and their values
predict_fn_populated
The prediction function populated with the parameter values
specification
A tibble::tbl_df of the model specification, which are the parameters and the descriptors together
FixedEffectsModel(
response = list(
hst = units::as_units("m")
),
covariates = list(
dsob = units::as_units("cm")
),
parameters = list(
beta_0 = 51.9954,
beta_1 = -0.0208,
beta_2 = 1.0182
),
predict_fn = function(dsob) {
1.37 + beta_0 * (1 - exp(beta_1 * dsob)^beta_2)
}
)
#> Model Call:
#> hst = f(dsob)
#>
#> hst [m]: total height of the stem
#> dsob [cm]: diameter of the stem, outside bark at breast height
#>
#> Parameter Estimates:
#> # A tibble: 1 × 3
#> beta_0 beta_1 beta_2
#> <dbl> <dbl> <dbl>
#> 1 52.0 -0.0208 1.02
#>
#> Model Descriptors:
#> # A tibble: 1 × 0